The continuous delayed distribution problem

作     者：Smirnov, Dina Herer, Yale T. Avrahami, Assaf 

作者机构：Eindhoven Univ Technol Sch Ind Engn Eindhoven Netherlands Technion Israel Inst Technol Fac Ind Engn & Management Haifa Israel EyeOn BV Aarle Rixtel Netherlands 

出 版 物：《COMPUTERS & OPERATIONS RESEARCH》 (计算机与运筹学研究)

年 卷 期：2022年第148卷

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Data-driven decision making One-warehouse multi-retailer Delayed distribution Multi-stage stochastic programming Subgradient optimization Infinitesimal perturbation analysis 

摘      要：Nowadays, decision makers (DMs) at companies have access to extensive and accurate data, which means they have the opportunity to grow and improve if they use the latent potential effectively. We address the complex problem of optimizing decisions in a multi-period one-warehouse multi-retailer inventory system with stochastic continuous demand and an option of delayed distributions. At the beginning of each period, the DM determines each retailer s target stock levels, as well as the number of items to be held back at a central location for later distribution(s). Such a policy offers partial inventory pooling through the holdback quantity. The decisions in each period are data-driven, i.e., made based on sales data available through an information system up to that point in time. We model the problem as a multi-stage stochastic program with recourse. For the general case, we develop a new recursive solution algorithm, which is based on subgradient optimization and an analysis of system dynamics. For the special case of two identical retailers and two periods, we provide explicit optimality conditions based on the subgradients. Using a large numerical study, we evaluate the performance of our proposed policy and compare it to two benchmark policies. We also demonstrate the impact of various problem parameters on the optimal solution and objective value.